This invention relates to assessing neurological conditions and more particularly to the diagnosis and monitoring of progression of dementia, the assessment of depression and the prediction of depression treatment efficacy. The invention may also be applied to diagnosing and monitoring epilepsy, Parkinson's disease, attention deficit (hyperactive) disorder, stroke, delirium, vigilance and sleep assessment.
Dementia is a generalized designation for a state of mental deterioration, manifested in cognitive dysfunction, such as memory loss, impaired thinking, and strange behavior. There are many types and causes of dementia, including vascular dementia, Alzheimer's type dementia (ATD), HIV/AIDS-related dementia, alcoholic dementia, depression, Huntington's disease, tumors and Parkinson's disease. ATD is the most common type of dementia and is a progressive, neurological disorder of the brain. ATD is the fourth leading cause of death in adults, after heart disease, cancer, and stroke.
Early diagnosis of ATD is desirable for several reasons. If the dementia is due to a cause other than Alzheimer's disease, it is often treatable. Identification of a cause other than Alzheimer's disease also relieves concern about the prognosis. Finally, a diagnosis of ATD at an early stage allows the afflicted and their family an opportunity for medical and financial planning. In addition, while the current treatment methods for ATD offer only short-term symptomatic relief, there are numerous treatments and prevention methods in development that promise a radically improved level of treatment. The widespread application of such therapies will require a much more effective method of diagnosing ATD in its earliest stages, before other symptoms have made their appearance. Even at present, early diagnosis is important to identify other symptomatically similar disease processes that are often easily treated and possibly reversed.
There is no definitive test for ATD; only by studying brain sections obtained during an autopsy may one conclusively arrive at a diagnosis of “definite ATD”. The most definitive diagnosis that may be obtained during the course of the illness is that of “probable Alzheimer's type dementia”. This diagnosis is typically arrived at by a rule-out procedure. Other disease processes that could produce similar symptoms are systematically ruled out using a standardized decision tree, generally the NINCDS-ADRDA criteria. This diagnosis of “probable ATD” is not always correct, however. When histopathological findings are compared with the clinical diagnosis following autopsy, it appears that 80–88% of clinical diagnoses are correct. The application of the NINCDS-ADRDA criteria is time-consuming and requires a degree of expertise that is not available to all general practitioners, internists and psychologists. Moreover, these methods are only applicable after the onset of symptoms such as memory loss and confusion.
Patients with dementia of many types (ATD, vascular, etc.) exhibit changes in EEG in comparison to age-matched normal subjects. Typical changes include increased EEG activity in the delta (0–4 Hz) and theta (4–8 Hz) bands and decreased EEG activity in the beta band (12–30 Hz). This is in contrast to elderly normal subjects, who exhibit decreased low frequency activity and increased high frequency activity with increasing age. In addition to differences between normal patients and those with dementia, there are characteristic changes in the EEG power spectra observed at progressively worsening levels of cerebral function, implying a progressive change in EEG parameters that may be used to stage the progression of the dementia. The change in theta power as a percent of the total power has been shown to distinguish between mild, moderate and severe dementia, as well as controls.
The EEG observed in patients with ATD exhibits specific characteristics that are different from those observed in cognitively normal, aged patients. Numerous published studies have reported on the analysis of electroencephalographic signals (EEG) with the objective of identifying patients with ATD. These studies and methods are generally designed to differentiate ATD patients from normal subjects and/or patients having dementias with similar symptoms but different etiologies, such as vascular infarcts. These methods generally utilize discriminant analyses or neural networks based upon various processed EEG parameters designed to quantify the changes in EEG typically observed in ATD (e.g., alpha power, the power observed in the 8–14 Hz band of the EEG power spectrum). The median accuracy of a variety of methods for differentiating ATD patients from cognitively normal controls in a series of 16 EEG studies was 81%, with a range of 54–100%. In general, these methods have reported sensitivities and specificities in the 80% range, approximately equivalent to that achievable by an expert clinician deriving a diagnosis from a clinical interview and history. However, it must be noted that in almost all studies the criteria used to differentiate normals from ATD were defined using the data in the analysis. There are few prospective studies that used a first population to develop a criterion and then applied that criterion to a second population. Thus, the actual accuracy of existing methods is difficult to determine.
Several investigators have proposed the use of a drug challenge for the assessment of dementia. Holschneider reported differential changes in the power in the 20–28 Hz spectral band in normal, ATD and vascular dementia subjects following administration of a thiopental bolus. While both normal and vascular dementia subjects showed significant increases in 20–28 Hz log power compared to baseline, the ATD subjects exhibited no change from baseline. Neufeld used a similar protocol to determine the differential effect of a dose of scopolamine between age-matched normal subjects and those with ATD. At baseline, ATD patients exhibited smaller absolute and relative alpha amplitudes (8–11.5 Hz) and larger relative theta amplitudes (4–7.5 Hz) compared with normal subjects. After intravenous administration of 0.5 mg scopolamine, the normal subjects exhibited a larger increase in absolute and relative delta amplitude (1–3.5 Hz) than the ATD subjects in comparison to a placebo. Scinto demonstrated a method of diagnosing Alzheimer's disease using an automated apparatus that can continuously monitor pupil diameter before and after the administration of a neural transmitter mediator to the targeted eye. The presence of hypersensitivity to the administered neural transmitter mediator serves as a marker of Alzheimer's disease.
Depression is a mood disorder that affects 17 million Americans each year, and is responsible for 9.7 million doctor visits. It affects sufferers in a variety of ways, resulting in depressed mood, irritability, sleep disorders, feelings of agitation; guilt and worthlessness, loss of energy and initiative, an inability to concentrate and an increased incidence of suicide. It is difficult to diagnose, due to comorbidities and the fact that it is largely self-reported. There are a number of antidepressant pharmacological agents, and once the proper treatment is determined, their effectiveness is quite high. Selection of the most efficacious agent and the initial dose is largely by trial and error. There is thus a need for an objective measure of depression as well as a method of predicting efficacy of antidepressant treatment. Diego, et al. found that the level of depression was correlated with frontal EEG alpha asymmetry and left frontal EEG alpha power. In another study, EEG theta activity was correlated with pre-treatment level of depression, and improved level of depression with treatment was correlated with slow (delta and theta) activity and fast (beta) activity at frontal recording sites. Still others have demonstrated that prefrontal EEG response to antidepressant medication therapy was seen as early as 48 hours after initiation of treatment and such changes preceded clinical response. These changes were absent in non-responders. Another earlier study reported small but statistically significant differences in pre-treatment theta power between responders and non-responders to an antidepressant medication. None of these methods have resulted in a device with high enough sensitivity and specificity to be clinically useful.
A commercially available device that uses bispectral analysis of the EEG is the Bispectral Index™ (BIS™). BIS is a univariate processed EEG parameter derived from surface electrodes placed on the forehead and temple. The Bispectral Index is described in U.S. Pat. Nos. 4,907,597; 5,010,891; 5,320,109 and 5,458,117, all of which are incorporated herein by reference. BIS is a complex parameter, consisting of a set of components that include power spectral and higher order (bispectral) components as well as time domain components. These components are combined into a single number scaled from 0 to 100. BIS has been designed to reflect the hypnotic state of an individual, both while awake and while undergoing anesthesia. In a patient under the influence of anesthetic agents, the probability of recall is closely related to the hypnotic state. For this reason, BIS is highly correlated with the probability of both free and cued recall in subjects under the influence of anesthetic and sedative agents. Decreased formation of new memories and an impaired ability to recall preexisting memories are hallmarks of various dementias. In certain progressive dementias, such as ATD, the degree of memory impairment increases as the disease progresses. BIS was observed to be lower at unmedicated, presurgical baseline in patients with dementia (ATD and multi-infarct dementia) compared to age-matched control subjects. It is well known that cerebral glucose metabolism is decreased in patients with ATD in comparison to age-matched patients with normal cognitive function. BIS was shown to be correlated with reduction of cerebral glucose metabolism resulting from anesthetic agents, as determined using positron emission tomography imaging. It is thus a reasonable conjecture that the one of the underlying technologies of BIS, bispectral analysis, might be useful in assessing neurological function in a global sense.